The object of this thesis was to develop a new approach of seasonal ocean wave forecasting for eight spots along the Atlantic coast of Western Europe during the winter months of December to February (DJF) with the initial date of 1st November. A main goal was to investigate the relationship between the mean DJF-significant wave height H1/3 and peak period Tpeak, respectively and the nSAI, the reciprocal value of the snow advance index (SAI). This index summarizes the daily rate of change of the snow cover extent in Eurasia for the month of October. Further goals were to predict forecasts of mean winter wave heights and wave periods and to compute probabilistic forecasts of exceedance of different thresholds, where the nSAI, the seasonal forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the combination of both were used as predictors.

The data for the predictands within the statistical models come from the ERA- Interim reanalysis for the winter seasons between 1997/98 and 2013/2014 and the models were based on the linear and ordered logistic regression. Furthermore, these models were verified and compared to each other and climate by the use of the ranked probability skill score (RPSS).

It was found that the north-easterly part of the North Atlantic showed values up to 0.75 and 0.69 for the correlation coefficients between the nSAI and the two mean DJF wave parameters H1/3 and Tpeak, respectively. For the southern part of the North Atlantic negative relationships between the nSAI and the two wave parameters were found.

The nSAI turned out to be an appropriate model predictor for seasonal forecasting models of winter waves for the majority of the investigated spots. Good model performances were especially found in the north-easterly part of the North Atlantic, where increasing nSAIs lead to increasing predicted probabilities of exceedance of certain thresholds of the two wave parameters. The models with the nSAI as in- put often outperformed the climate and the models based on the ECMWF seasonal forecasts. Moreover, the climate outperformed the postprocessed DJF-ECMWF seasonal forecasts at five spots for the models of H1/3 and at all of the eight spots for the Tpeak-models.